Crm Segmentation And Clustering Using Sas Enterprise Miner

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CRM Segmentation and Clustering Using SAS Enterprise Miner

Author : Randall S. Collica
Publisher : SAS Press
ISBN 13 : 9781590475089
Total Pages : 0 pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis CRM Segmentation and Clustering Using SAS Enterprise Miner by : Randall S. Collica

Download or read book CRM Segmentation and Clustering Using SAS Enterprise Miner written by Randall S. Collica and published by SAS Press. This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the customer is critical to your company's success. In this instructive guide, Randy Collica employs SAS Enterprise Miner and the most commonly available techniques for customer relationship management (CRM). You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want. Step-by-step examples and exercises clearly illustrate the concepts of segmentation and clustering in the context of CRM. The book, with a foreword by Michael J. A. Berry, is sectioned into three parts. Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries. Part 2 offers an in-depth treatment of segmentation with practical topics such as when and how to update your models and clustering with many attributes. Part 3 goes beyond traditional segmentation practices to introduce recommended strategies for clustering product affinities, handling missing data, and incorporating textual records into your predictive model with SAS Text Miner software.This straight-forward guide will appeal to anyone who seeks to better understand customers or prospective customers. Additionally, professors and students will find the book well suited for a business data mining analytics course in an MBA program or related course of study. You should understand basic statistics, but no prior knowledge of data mining or SAS Enterprise Miner is required. Included on your bonus CD-ROM are the following: example SAS code, data sets, macros, and Enterprise Miner templates.

Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition

Author : Randall S. Collica
Publisher : SAS Press
ISBN 13 : 9781607648109
Total Pages : 0 pages
Book Rating : 4.6/5 (481 download)

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Book Synopsis Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition by : Randall S. Collica

Download or read book Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition written by Randall S. Collica and published by SAS Press. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prev. ed. published under title: CRM segmentation and clustering using SAS Enterprise miner.

CRM Segmentation and Clustering Using SAS(R) Enterprise Miner(TM)

Author : Randall S. Collica
Publisher :
ISBN 13 : 9781599948317
Total Pages : pages
Book Rating : 4.9/5 (483 download)

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Book Synopsis CRM Segmentation and Clustering Using SAS(R) Enterprise Miner(TM) by : Randall S. Collica

Download or read book CRM Segmentation and Clustering Using SAS(R) Enterprise Miner(TM) written by Randall S. Collica and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition

Author : Randall S. Collica
Publisher : SAS Institute
ISBN 13 : 1629605298
Total Pages : 356 pages
Book Rating : 4.6/5 (296 download)

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Book Synopsis Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition by : Randall S. Collica

Download or read book Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition written by Randall S. Collica and published by SAS Institute. This book was released on 2017-03-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Résumé : A working guide that uses real-world data, this step-by-step resource will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. --

Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition, 2nd Edition

Author : Randy Collica
Publisher :
ISBN 13 :
Total Pages : 378 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition, 2nd Edition by : Randy Collica

Download or read book Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition, 2nd Edition written by Randy Collica and published by . This book was released on 2011 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the customer is critical to your company's success. In this book, Randy Collica employs SAS Enterprise Miner and the most commonly available techniques for customer relationship management (CRM). You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want.

Customer Segmentation and Clustering Using SAS Enterprise Miner

Author : Randall S. Collica
Publisher :
ISBN 13 : 9781606748107
Total Pages : 0 pages
Book Rating : 4.7/5 (481 download)

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Book Synopsis Customer Segmentation and Clustering Using SAS Enterprise Miner by : Randall S. Collica

Download or read book Customer Segmentation and Clustering Using SAS Enterprise Miner written by Randall S. Collica and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data Mining Techniques in CRM

Author : Konstantinos K. Tsiptsis
Publisher : John Wiley & Sons
ISBN 13 : 1119965454
Total Pages : 288 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Data Mining Techniques in CRM by : Konstantinos K. Tsiptsis

Download or read book Data Mining Techniques in CRM written by Konstantinos K. Tsiptsis and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.

Text Mining and Analysis

Author : Dr. Goutam Chakraborty
Publisher : SAS Institute
ISBN 13 : 1612907873
Total Pages : 340 pages
Book Rating : 4.6/5 (129 download)

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Book Synopsis Text Mining and Analysis by : Dr. Goutam Chakraborty

Download or read book Text Mining and Analysis written by Dr. Goutam Chakraborty and published by SAS Institute. This book was released on 2014-11-22 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program.

Data Mining Techniques. Segmentation with SAS Enterprise Miner

Author : Scientific Books
Publisher : CreateSpace
ISBN 13 : 9781512098006
Total Pages : 288 pages
Book Rating : 4.0/5 (98 download)

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Book Synopsis Data Mining Techniques. Segmentation with SAS Enterprise Miner by : Scientific Books

Download or read book Data Mining Techniques. Segmentation with SAS Enterprise Miner written by Scientific Books and published by CreateSpace. This book was released on 2015-05-08 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused segmentation tasks. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute. The essential content of the book is as follows: SAS ENTERPRISE MINER WORKING ENVIRONMENTSEGMENTATION PREDICTIVE TECHNIQUES MODELING PREDICTIVE TECHNIQUES FOR SEGMENTATION REGRESSION NODE: MULTIPLE REGRESSION MODEL LOGISTIC REGRESSION DMINE REGRESSION NODE SEGMENTATION PREDICTIVE TECHNIQUES. DECISION TREES DECISION TREE NODE DECISION TREE INTERACTIVE TRAINING DECISION TREE NODE OUTPUT DATA SOURCES GRADIENT BOOSTING NODE SEGMENTATION PREDICITIVE MODELS WITH NEURAL NETWORKS NEURAL NETWORKS FOR SEGMENTATION OPTIMIZATION AND ADJUSTMENT OF SEGMENTATION MODELS WITH NETS: NEURAL NETWORK NODE SIMPLE NEURAL NETWORKS PERCEPTRONS HIDDEN LAYERS MULTILAYER PERCEPTRONS (MLPS) RADIAL BASIS FUNCTION (RBF) NETWORKS LOCAL PROCESSING NETWORKS SCORING NEURAL NETWORK NODE TRAIN PROPERTIES NEURAL NETWORK NODE RESULTS AUTONEURAL NODE NETWORK ARCHITECTURES DM NEURAL NODE ENSEMBLE NODE SEGMENTATION DESCRIPTIVE TECHNIQUES. CLUSTER ANALYSIS CLUSTER ANALYSIS ON ENTERPRISE MINER CLUSTER NODE SOM/KOHONEN NODE VARIABLE CLUSTERING NODE PREDICTIVE MODELING WITH VARIABLE CLUSTERING EXAMPLE ASSESS PHASE IN SEGMENTATION PREDICTIVE MODELS CUTOFF NODE SCORE NODE SEGMENT PROFILE NODE

Predictive Marketing

Author : Omer Artun
Publisher : John Wiley & Sons
ISBN 13 : 1119037336
Total Pages : 217 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Predictive Marketing by : Omer Artun

Download or read book Predictive Marketing written by Omer Artun and published by John Wiley & Sons. This book was released on 2015-08-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT

Author : Michael J. A. Berry
Publisher :
ISBN 13 : 9788126518258
Total Pages : 512 pages
Book Rating : 4.5/5 (182 download)

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Book Synopsis MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT by : Michael J. A. Berry

Download or read book MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT written by Michael J. A. Berry and published by . This book was released on 2008-09-01 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers.

Statistical and Machine-Learning Data Mining:

Author : Bruce Ratner
Publisher : CRC Press
ISBN 13 : 149879761X
Total Pages : 690 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Statistical and Machine-Learning Data Mining: by : Bruce Ratner

Download or read book Statistical and Machine-Learning Data Mining: written by Bruce Ratner and published by CRC Press. This book was released on 2017-07-12 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Customer Relationship Management

Author : Francis Buttle
Publisher : Routledge
ISBN 13 : 1856175227
Total Pages : 495 pages
Book Rating : 4.8/5 (561 download)

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Book Synopsis Customer Relationship Management by : Francis Buttle

Download or read book Customer Relationship Management written by Francis Buttle and published by Routledge. This book was released on 2009 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title presents an holistic view of CRM, arguing that its essence concerns basic business strategy - developing and maintaining long-term, mutually beneficial relationships with strategically significant customers - rather than the operational tools which achieve these aims.

Data Mining and Statistics for Decision Making

Author : Stéphane Tufféry
Publisher : John Wiley & Sons
ISBN 13 : 0470979283
Total Pages : 748 pages
Book Rating : 4.4/5 (79 download)

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Book Synopsis Data Mining and Statistics for Decision Making by : Stéphane Tufféry

Download or read book Data Mining and Statistics for Decision Making written by Stéphane Tufféry and published by John Wiley & Sons. This book was released on 2011-03-23 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Enterprise Cloud Strategy

Author : Barry Briggs
Publisher : Microsoft Press
ISBN 13 : 1509301992
Total Pages : 228 pages
Book Rating : 4.5/5 (93 download)

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Book Synopsis Enterprise Cloud Strategy by : Barry Briggs

Download or read book Enterprise Cloud Strategy written by Barry Briggs and published by Microsoft Press. This book was released on 2016-01-07 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage.

Applied Analytics through Case Studies Using SAS and R

Author : Deepti Gupta
Publisher : Apress
ISBN 13 : 1484235258
Total Pages : 415 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Applied Analytics through Case Studies Using SAS and R by : Deepti Gupta

Download or read book Applied Analytics through Case Studies Using SAS and R written by Deepti Gupta and published by Apress. This book was released on 2018-08-03 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Author : Cengiz Kahraman
Publisher : Springer
ISBN 13 : 3030237567
Total Pages : 1392 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making by : Cengiz Kahraman

Download or read book Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making written by Cengiz Kahraman and published by Springer. This book was released on 2019-07-05 with total page 1392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.